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Marina Vabistsevits
Doctoral student at the University of Bristol, working in the interdisciplinary research of applying data mining methods to answer epidemiological questions
Education
PhD, Data mining in Epidemiology
University of Bristol
Bristol, UK
2023 - 2019
MSc, Bioinformatics
University of Copenhagen
Copenhagen, Denmark
2017 - 2015
BSc, Biochemistry
University of Bath
Bath, UK
2015 - 2011
Research Experience
Doctoral Student
MRC Intergative Epidemiology Unit
University of Bristol
2023 - 2019
- Mini-project 1: Implemented multivariate correlation analysis workflow in R (metaCCA) using OpenGWAS data, to find pleiotropic variants across multiple traits
- Mini-project 2: Carried out a Mendelian Randomisation study to investigate the mechanism mediating the effect of early life BMI on breast cancer risk
- PhD project: Working with EpiGraphDB, a Neo4j graph database, to answer causal relationship questions in breast cancer and build a comprehensive model of the disease aetiology, by applying data mining and machine learning methods
Visiting Researcher / Master’s Thesis Student
Danish Cancer Research Centre
Copenhagen, Denmark
2017 - 2016
- Explored TCGA breast cancer gene expression RNA-Seq data to identify the involvement of autophagy-related genes in certain disease subtypes.
- Performed extensive EDA, followed by differential expression analysis and enrichment analysis, allowing me to find over-represented autophagy genes
Industry Experience
Bioinformatician
Living DNA
Frome, UK
2019 - 2017
- Led the research work on improving the ancestry reference panels used by the core pipeline behind the company’s direct-to-consumer ancestry genetics test, bringing considerable improvement to results accuracy
- Gained experience in working with a legacy codebase through maintaining and contributing to the in-house pipelines (Python)
- Honed my R programming skills by switching to tidyverse approach and advanced my data visualisation skills
Student research assistant in the Big Data group
3Shape
Copenhagen, Denmark
2017 - 2016
- Performed data preparation and visualisation tasks in Python, gaining practical experience of programming in a professional environment
- Used deep learning framework Caffe2 to develop a neural network training pipeline for scan image classification tasks
Placement Student in Bioinformatics team
Oxford Gene Technology
Oxford, UK
2014 - 2013
- Became responsible for a multitude of exome- and RNA-seq projects, running in-house data analysis pipelines and performing custom analysis for different projects